A primer on p-value thresholds and α-levels – two different kettles of fish

Norbert Hirschauer, Sven Gruener, Oliver Musshoff and Claudia Becker

No d46m2_v1, SocArXiv from Center for Open Science

Abstract: It has often been noted that the “null-hypothesis-significance-testing” (NHST) framework is an inconsistent hybrid of Neyman-Pearson’s “hypotheses testing” and Fisher’s “significance test-ing” approach that almost inevitably causes misinterpretations. To facilitate a realistic assessment of the potential and the limits of statistical inference, we briefly recall widespread inferential errors and outline the two original approaches of these famous statisticians. Based on the under-standing of their irreconcilable perspectives, we propose “going back to the roots” and using the initial evidence in the data in terms of the size and the uncertainty of the estimate for the pur-pose of statistical inference. Finally, we make six propositions that hopefully contribute to im-proving the quality of inferences in future research.

Date: 2020-09-23
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Related works:
Journal Article: A Primer on p-Value Thresholds and α-Levels – Two Different Kettles of Fish (2021)
Working Paper: A primer on p-value thresholds and α-levels – two different kettles of fish (2020)
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Persistent link: https://EconPapers.repec.org/RePEc:osf:socarx:d46m2_v1

DOI: 10.31219/osf.io/d46m2_v1

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